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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Heterogeneity of the GFP fitness landscape and data-driven protein design
Louisa González Somermeyer, Aubin Fleiss, Alexander S. Mishin, et al.
eLife (2022) Vol. 11
Open Access | Times Cited: 42

Showing 1-25 of 42 citing articles:

ProteinGym: Large-Scale Benchmarks for Protein Design and Fitness Prediction
Pascal Notin, Aaron W. Kollasch, Daniel P. Ritter, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 77
Simulating 500 million years of evolution with a language model
Thomas Hayes, Roshan Rao, Halil Akin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Closed Access | Times Cited: 76
Simulating 500 million years of evolution with a language model
Thomas Hayes, Roshan Rao, Halil Akin, et al.
Science (2025)
Open Access | Times Cited: 5
Optimization strategies and advances in the research and development of AAV‐based gene therapy to deliver large transgenes
Valeria V. Kolesnik, Ruslan F. Nurtdinov, Ezekiel S. Oloruntimehin, et al.
Clinical and Translational Medicine (2024) Vol. 14, Iss. 3
Open Access | Times Cited: 8
A combinatorially complete epistatic fitness landscape in an enzyme active site
Kadina E. Johnston, Patrick J. Almhjell, Ella J. Watkins‐Dulaney, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 32
Open Access | Times Cited: 8
A map of the rubisco biochemical landscape
Noam Prywes, Naiya R. Phillips, Luke M. Oltrogge, et al.
Nature (2025)
Open Access
Learning Epistasis and Residue Coevolution Patterns: Current Trends and Future Perspectives for Advancing Enzyme Engineering
Marcel Wittmund, Frédéric Cadet, Mehdi D. Davari
ACS Catalysis (2022) Vol. 12, Iss. 22, pp. 14243-14263
Closed Access | Times Cited: 34
Higher-order epistasis and phenotypic prediction
Juannan Zhou, Mandy S. Wong, Wei-Chia Chen, et al.
Proceedings of the National Academy of Sciences (2022) Vol. 119, Iss. 39
Open Access | Times Cited: 26
Learning protein fitness landscapes with deep mutational scanning data from multiple sources
Lin Chen, Zehong Zhang, Zhenghao Li, et al.
Cell Systems (2023) Vol. 14, Iss. 8, pp. 706-721.e5
Open Access | Times Cited: 19
Designed active-site library reveals thousands of functional GFP variants
Jonathan J. Weinstein, Carlos Martí‐Gómez, Rosalie Lipsh‐Sokolik, et al.
Nature Communications (2023) Vol. 14, Iss. 1
Open Access | Times Cited: 18
In vitro continuous protein evolution empowered by machine learning and automation
Tianhao Yu, Aashutosh Girish Boob, Nilmani Singh, et al.
Cell Systems (2023) Vol. 14, Iss. 8, pp. 633-644
Closed Access | Times Cited: 18
Structure‐ and Data‐Driven Protein Engineering of Transaminases for Improving Activity and Stereoselectivity
Yu‐Fei Ao, Shuxin Pei, Chao Xiang, et al.
Angewandte Chemie International Edition (2023) Vol. 62, Iss. 23
Open Access | Times Cited: 17
Rugged fitness landscapes minimize promiscuity in the evolution of transcriptional repressors
Anthony Meger, Matthew A. Spence, Mahakaran Sandhu, et al.
Cell Systems (2024) Vol. 15, Iss. 4, pp. 374-387.e6
Open Access | Times Cited: 5
Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space
Marshall Case, Matthew Smith, Jordan Vinh, et al.
Proceedings of the National Academy of Sciences (2024) Vol. 121, Iss. 11
Open Access | Times Cited: 4
Enhancers display constrained sequence flexibility and context-specific modulation of motif function
Franziska Reiter, Bernardo P. de Almeida, Alexander Stark
Genome Research (2023) Vol. 33, Iss. 3, pp. 346-358
Open Access | Times Cited: 12
Machine Learning for Protein Engineering
Kadina E. Johnston, Clara Fannjiang, Bruce J. Wittmann, et al.
Challenges and advances in computational chemistry and physics (2023), pp. 277-311
Closed Access | Times Cited: 11
EvoAI enables extreme compression and reconstruction of the protein sequence space
Shuyi Zhang, Zi-yuan Ma, Wenjie Li, et al.
Research Square (Research Square) (2024)
Open Access | Times Cited: 3
Removing bias in sequence models of protein fitness
Ada Y. Shaw, Hansen Spinner, June Shin, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 9
ProteinNPT: Improving Protein Property Prediction and Design with Non-Parametric Transformers
Pascal Notin, Ruben Weitzman, Debora S. Marks, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 8
A combinatorially complete epistatic fitness landscape in an enzyme active site
Kadina E. Johnston, Patrick J. Almhjell, Ella J. Watkins‐Dulaney, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 2
EvoAI enables extreme compression and reconstruction of the protein sequence space
Zi-yuan Ma, Wenjie Li, Yunhao Shen, et al.
Nature Methods (2024)
Open Access | Times Cited: 2
Interpretable and explainable predictive machine learning models for data-driven protein engineering
David Medina-Ortiz, Ashkan Khalifeh, Hoda Anvari-Kazemabad, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
Discovering genotype–phenotype relationships with machine learning and the Visual Physiology Opsin Database (VPOD)
Seth A. Frazer, Mahdi Baghbanzadeh, Ali Rahnavard, et al.
GigaScience (2024) Vol. 13
Open Access | Times Cited: 1
Fitness Landscape Analysis of a tRNA Gene Reveals that the Wild Type Allele is Sub-optimal, Yet Mutationally Robust
Tzahi Gabzi, Yitzhak Pilpel, Tamar Friedlander
Molecular Biology and Evolution (2022) Vol. 39, Iss. 9
Open Access | Times Cited: 8
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